How to Maintain a Clinical Research Data Warehouse
- Category: Clinical Research Data Warehouse
- Published: Tuesday, 26 February 2019 16:12
- Written by Data Help
- Hits: 1005
A Clinical Research Data Warehouse is a data warehouse that caters to the needs of clinical researchers. Clinical research is a branch of medicine that determines the safety of all medical products such as medication, medical devices, diagnostic products, and even treatment plans and regimens. Clinical research helps oversee, in their own way, the prevention, treatment, diagnosis of diseases and their symptoms. A Clinical Research Data Warehouse requires maintenance and in order to do this efficiently, a healthcare organization needs to have the right manpower, the right team, the right tools, the right systems, and procedures etc. We discuss these below-->
The Clinical Research Data Warehouse Team Management
In order to have a properly run and efficient clinical research data warehouse, there has to be a well-versed team put in charge of making this happen. This team will help run the data warehouse smoothly and will serve as a great compliment to the existing technology. The team will also be in charge of analyzing and interpreting the data to obtain meaningful insight for clinical research purposes. The team should be given the right tools to work with the data. When it comes to clinical research data which can be quite sensitive, there can be many possible points of breeches which can lead to data loss or data compromisation. Thus the team should be properly trained and should receive regular training so they are always up to dat with he rapidly evolving and dynamic industry of data management, data storage, and data technology
The Clinical Research Data Warehouse Tools
Even with a highly skilled team, they still need the right data management tools, software, hardware, technology, devices etc in order for them to do their jobs efficiently. Not only does this technology have to be available, but it also has to be up to date and up to standard. The wrong technology or inefficient technology can lead to errors and mistakes that could cause a lot of damage to the clinical data warehouse. Malfunctioning technology can corrupt the data, cause glitches, and even prevent access to the data. We all know that even the most up to date and robust data is useless if it cannot be accessed as and when needed.
Thus, all data management tools should help the data management team do their jobs better and should not hinder them or make their job more difficult. Data management tools and technology should reduce the possibility of human errors and should make data processing faster and more efficient. The data management tools should also be able to point out errors in the system in real time and should fix the errors or make suggestions on how the error can be fixed. For example, Google Search Index, can scan a website and point out possible problems and errors in the pages. One of those can be AMP problems. If there is an Accelerated Mobile Page not functioning well in the site, then it can be pointed out by the Google bots and then it leaves suggestions on how it can be fixed. That way the human managing the site( the data management team) takes these steps to fix the problematic page.
Using a Clinical Research Data Warehouse
It's not enough to store data efficiently, it must also be put to use for day to day activities, long term planning, and for strategic goal setting within a clinical research facility. Data can be out to work in different ways depending on the need. For example with automation parameters can be set for the data which will automate most things. Automation is not just for mundane actions. with artificial intelligence becoming more and more advanced, automatic able set to do some very advanced things. Artificial intelligence techniques can be used to identify high priority risks before they happen and take a=ction to prevent these risks from occurring. Artificial intelligence data monitoring and customization can track pattern, trends, anomalies, outliers, and irregularities in the data.
The Future of Clinical Research Data Warehouse
As data tools become more advanced and Artificial Intelligence continues to evolve, so will its capabilities. Thus the human element will have more time to focus on other aspects of data uses and applications. As with most things related to data and technology, clinical research data warehouse faces many possibilities. As data research continues to and be more advanced thanks to the infusion with technology, more and more innovations are starting to pup up and they are becoming bolder. In the marketing industry, for example, data research is used for consumer targeting and retargeting.
Companies seek to understand the patterns and buying habits of their customers so they can do more direct selling with a high percentage success rate. Another is is the are of emerging currencies. Cryptocurrency promises to offer a solution to a problem that is not yet a problem. And while there are lots of speculations on its viability and also taking into consideration how volatile it is, many people still are paying close attention to it. Some industries and companies see it as a way to get ahead in the data field and be an industry leader. Whatever the case, clinical research data warehouses are not the same as they were 10 years ago and the changes and advancements are becoming less far between and bolder.